يعرض 101 - 120 نتائج من 3,127 نتيجة بحث عن '(((( algorithm python function ) OR ( algorithm pca function ))) OR ( algorithm both function ))', وقت الاستعلام: 0.42s تنقيح النتائج
  1. 101

    Parselmouth for bioacoustics: automated acoustic analysis in Python حسب Yannick Jadoul (11498813)

    منشور في 2023
    "…Five years ago, the Python package Parselmouth was released to provide easy and intuitive access to all functionality in the Praat software. …"
  2. 102

    Prediction performance of different optimization algorithms. حسب Ali-Kemal Aydin (10968731)

    منشور في 2021
    "…<p>(A) 3 algorithms were compared in terms of the residuals of the cost function of the optimized TF on 7 mice datasets (Derivative free algorithm failed in optimizing a TF in a mouse). …"
  3. 103
  4. 104

    Comparison of different algorithms. حسب Dawei Wang (471687)

    منشور في 2025
    "…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"
  5. 105
  6. 106

    Study proposed algorithm. حسب Ainhoa Pérez-Guerrero (21377457)

    منشور في 2025
    "…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …"
  7. 107
  8. 108

    ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space حسب Koushik Naskar (7510592)

    منشور في 2020
    "…In order to overcome such shortcoming, we develop a generalized algorithm, “ADT” to generate the nonadiabatic equations through symbolic manipulation and to construct highly accurate diabatic surfaces for molecular processes involving excited electronic states. …"
  9. 109
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  13. 113

    Algorithm of the brightness scale calibration experiment. حسب Krzysztof Petelczyc (3954203)

    منشور في 2024
    "…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …"
  14. 114

    Gillespie algorithm simulation parameters. حسب Nicholas H. Vitale (20469289)

    منشور في 2024
    "…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …"
  15. 115

    Scheduling time of five algorithms. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
  16. 116

    Convergence speed of five algorithms. حسب Huichao Guo (14515171)

    منشور في 2025
    "…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"
  17. 117
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    Multi-algorithm comparison figure. حسب Dawei Wang (471687)

    منشور في 2025
    "…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"
  19. 119

    Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy حسب Yujin Wu (2901128)

    منشور في 2021
    "…We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. …"
  20. 120

    Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy حسب Yujin Wu (2901128)

    منشور في 2021
    "…We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. …"